{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9c4b370c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import xlwt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c643cbc",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 等宽分箱操作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "05f12cdc",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>男1000米跑</th>\n",
       "      <th>男1000米跑分数</th>\n",
       "      <th>男50米跑</th>\n",
       "      <th>男50米跑分数</th>\n",
       "      <th>男跳远</th>\n",
       "      <th>男跳远分数</th>\n",
       "      <th>男体前屈</th>\n",
       "      <th>男体前屈分数</th>\n",
       "      <th>男引体</th>\n",
       "      <th>男引体分数</th>\n",
       "      <th>男肺活量</th>\n",
       "      <th>男肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.13</td>\n",
       "      <td>72</td>\n",
       "      <td>8.88</td>\n",
       "      <td>66</td>\n",
       "      <td>195</td>\n",
       "      <td>60</td>\n",
       "      <td>12</td>\n",
       "      <td>74</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2785</td>\n",
       "      <td>62</td>\n",
       "      <td>170</td>\n",
       "      <td>72.599998</td>\n",
       "      <td>25.120001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.16</td>\n",
       "      <td>70</td>\n",
       "      <td>7.70</td>\n",
       "      <td>78</td>\n",
       "      <td>225</td>\n",
       "      <td>74</td>\n",
       "      <td>11</td>\n",
       "      <td>74</td>\n",
       "      <td>7</td>\n",
       "      <td>60</td>\n",
       "      <td>3133</td>\n",
       "      <td>68</td>\n",
       "      <td>174</td>\n",
       "      <td>52.700001</td>\n",
       "      <td>17.410000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.09</td>\n",
       "      <td>74</td>\n",
       "      <td>8.45</td>\n",
       "      <td>70</td>\n",
       "      <td>218</td>\n",
       "      <td>70</td>\n",
       "      <td>14</td>\n",
       "      <td>78</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3901</td>\n",
       "      <td>80</td>\n",
       "      <td>169</td>\n",
       "      <td>46.500000</td>\n",
       "      <td>16.280001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.21</td>\n",
       "      <td>68</td>\n",
       "      <td>8.05</td>\n",
       "      <td>74</td>\n",
       "      <td>206</td>\n",
       "      <td>64</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4946</td>\n",
       "      <td>100</td>\n",
       "      <td>183</td>\n",
       "      <td>79.699997</td>\n",
       "      <td>23.799999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>3.44</td>\n",
       "      <td>85</td>\n",
       "      <td>7.52</td>\n",
       "      <td>78</td>\n",
       "      <td>210</td>\n",
       "      <td>66</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>9</td>\n",
       "      <td>68</td>\n",
       "      <td>3538</td>\n",
       "      <td>74</td>\n",
       "      <td>171</td>\n",
       "      <td>54.700001</td>\n",
       "      <td>18.709999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>4.23</td>\n",
       "      <td>68</td>\n",
       "      <td>8.27</td>\n",
       "      <td>72</td>\n",
       "      <td>208</td>\n",
       "      <td>66</td>\n",
       "      <td>10</td>\n",
       "      <td>72</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4647</td>\n",
       "      <td>100</td>\n",
       "      <td>176</td>\n",
       "      <td>69.500000</td>\n",
       "      <td>22.440001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>5.19</td>\n",
       "      <td>40</td>\n",
       "      <td>9.55</td>\n",
       "      <td>50</td>\n",
       "      <td>210</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
       "      <td>80</td>\n",
       "      <td>6</td>\n",
       "      <td>50</td>\n",
       "      <td>7042</td>\n",
       "      <td>100</td>\n",
       "      <td>177</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>24.260000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>3.25</td>\n",
       "      <td>100</td>\n",
       "      <td>7.50</td>\n",
       "      <td>80</td>\n",
       "      <td>252</td>\n",
       "      <td>90</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>13</td>\n",
       "      <td>85</td>\n",
       "      <td>5755</td>\n",
       "      <td>100</td>\n",
       "      <td>181</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>19.840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>4.39</td>\n",
       "      <td>62</td>\n",
       "      <td>7.81</td>\n",
       "      <td>76</td>\n",
       "      <td>208</td>\n",
       "      <td>66</td>\n",
       "      <td>14</td>\n",
       "      <td>78</td>\n",
       "      <td>11</td>\n",
       "      <td>76</td>\n",
       "      <td>5688</td>\n",
       "      <td>100</td>\n",
       "      <td>172</td>\n",
       "      <td>51.700001</td>\n",
       "      <td>17.480000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>477 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     班级 性别  男1000米跑  男1000米跑分数  男50米跑  男50米跑分数  男跳远  男跳远分数  男体前屈  男体前屈分数  男引体  \\\n",
       "0     1  男     4.13         72   8.88       66  195     60    12      74    1   \n",
       "1     1  男     4.16         70   7.70       78  225     74    11      74    7   \n",
       "2     1  男     4.09         74   8.45       70  218     70    14      78    1   \n",
       "3     1  男     4.21         68   8.05       74  206     64    13      76    1   \n",
       "4     1  男     3.44         85   7.52       78  210     66    13      76    9   \n",
       "..   .. ..      ...        ...    ...      ...  ...    ...   ...     ...  ...   \n",
       "472  17  男     4.23         68   8.27       72  208     66    10      72    0   \n",
       "473  17  男     5.19         40   9.55       50  210     66    15      80    6   \n",
       "474  17  男     3.25        100   7.50       80  252     90    13      76   13   \n",
       "475  17  男     4.39         62   7.81       76  208     66    14      78   11   \n",
       "476  17  男     0.00          0   0.00        0    0      0     0       0    0   \n",
       "\n",
       "     男引体分数  男肺活量  男肺活量分数   身高         体重        BMI  \n",
       "0        0  2785      62  170  72.599998  25.120001  \n",
       "1       60  3133      68  174  52.700001  17.410000  \n",
       "2        0  3901      80  169  46.500000  16.280001  \n",
       "3        0  4946     100  183  79.699997  23.799999  \n",
       "4       68  3538      74  171  54.700001  18.709999  \n",
       "..     ...   ...     ...  ...        ...        ...  \n",
       "472      0  4647     100  176  69.500000  22.440001  \n",
       "473     50  7042     100  177  76.000000  24.260000  \n",
       "474     85  5755     100  181  65.000000  19.840000  \n",
       "475     76  5688     100  172  51.700001  17.480000  \n",
       "476      0     0       0    0   0.000000   0.000000  \n",
       "\n",
       "[477 rows x 17 columns]"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "male = pd.read_excel(r'C:\\Users\\Mr.Xiao\\Desktop\\体测分数_男生.xls',header=0,index_col=False,sheet_name=0)\n",
    "male"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ecbc4b51",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "       17, 18, 19, 20, 21, 23], dtype=int64)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f = male['男引体'].unique()\n",
    "f.sort()\n",
    "f.size#先查看样本整体范围是0-23，共23个数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f892b4ca",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "male_bin =pd.cut(male['男引体'],bins=[0,8,16,24],right=False,labels=['差','中','优'])\n",
    "male_distribution = male_bin.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "9240f414",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '男生引体成绩分布')"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,7))\n",
    "plt.rcParams['font.family']='Microsoft Yahei'\n",
    "_=plt.pie(male_distribution,labels=male_distribution.index,explode=[0,0,0.1],pctdistance=0.8,textprops={'fontsize':15},\n",
    "          shadow=True,autopct='%0.2f%%')\n",
    "plt.legend()\n",
    "plt.title(label='男生引体成绩分布',color='white',backgroundcolor='black',fontsize=18,pad=20,weight='bold')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "83ed388f",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.        , 3.00999999, 3.01999998, 3.02999997, 3.03999996,\n",
       "       3.04999995, 3.1400001 , 3.1500001 , 3.16000009, 3.17000008,\n",
       "       3.19000006, 3.21000004, 3.22000003, 3.24000001, 3.25      ,\n",
       "       3.26999998, 3.27999997, 3.28999996, 3.31999993, 3.32999992,\n",
       "       3.33999991, 3.36999989, 3.38000011, 3.3900001 , 3.41000009,\n",
       "       3.42000008, 3.43000007, 3.44000006, 3.45000005, 3.46000004,\n",
       "       3.47000003, 3.48000002, 3.49000001, 3.50999999, 3.51999998,\n",
       "       3.52999997, 3.53999996, 3.54999995, 3.55999994, 3.56999993,\n",
       "       3.57999992, 3.58999991, 4.        , 4.01000023, 4.01999998,\n",
       "       4.03000021, 4.03999996, 4.05000019, 4.05999994, 4.07000017,\n",
       "       4.07999992, 4.09000015, 4.0999999 , 4.11000013, 4.11999989,\n",
       "       4.13000011, 4.13999987, 4.1500001 , 4.15999985, 4.17000008,\n",
       "       4.17999983, 4.19000006, 4.21000004, 4.21999979, 4.23000002,\n",
       "       4.23999977, 4.25      , 4.26000023, 4.26999998, 4.28000021,\n",
       "       4.28999996, 4.30999994, 4.32000017, 4.32999992, 4.34000015,\n",
       "       4.3499999 , 4.36000013, 4.36999989, 4.38000011, 4.38999987,\n",
       "       4.40999985, 4.42000008, 4.44000006, 4.44999981, 4.46000004,\n",
       "       4.48000002, 4.48999977, 4.51000023, 4.51999998, 4.53000021,\n",
       "       4.53999996, 4.55999994, 4.57999992, 4.59000015, 4.61000013,\n",
       "       4.63000011, 4.63999987, 4.65999985, 4.67999983, 5.01999998,\n",
       "       5.03000021, 5.05000019, 5.05999994, 5.19000006, 5.26000023,\n",
       "       5.28000021, 5.28999996, 5.32000017, 5.32999992, 5.46999979])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f = male['男1000米跑'].unique()\n",
    "f.sort()\n",
    "f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "cb9636a8",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "male_bin =pd.cut(male['男1000米跑'],bins=3,right=False,labels=['差','中','优'])\n",
    "male_distribution = male_bin.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "d7a86bd2",
   "metadata": {
    "hidden": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '男生1000米跑分布')"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,7))\n",
    "plt.rcParams['font.family']='Microsoft Yahei'\n",
    "_=plt.pie(male_distribution,labels=male_distribution.index,explode=[0,0,0.1],pctdistance=0.8,textprops={'fontsize':15},\n",
    "          shadow=True,autopct='%0.2f%%')\n",
    "plt.legend()\n",
    "plt.title(label='男生1000米跑分布',color='white',backgroundcolor='black',fontsize=18,pad=20,weight='bold')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "536528b5",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 直方图统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "id": "26fb5c86",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "female = pd.read_excel(r'C:\\Users\\Mr.Xiao\\Desktop\\体测分数_女生.xls')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "id": "cd2e5cf3",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "female_800= pd.cut(female['女800米跑分数'],bins=[0,60,75,90,100],labels=['不合格','合格','良好','优秀'])\n",
    "female_800 = pd.DataFrame(female_800)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 405,
   "id": "e571e596",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "female_jump= pd.cut(female['女跳远分数'],bins=[0,60,75,90,100],labels=['不合格','合格','良好','优秀'])\n",
    "female_jump = pd.DataFrame(female_jump)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35eeada4",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 406,
   "id": "d0f29ea5",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,7))\n",
    "\n",
    "plt1 =score_800 =female_800.value_counts()\n",
    "plt2 =score_jump = female_jump.value_counts()\n",
    "\n",
    "fig1=plt.bar(x=np.arange(1,5)-0.15,height=score_800,width=0.3)\n",
    "fig2=plt.bar(x=np.arange(1,5)+0.15,height=score_jump,width=0.3)\n",
    "plt.xticks(np.arange(1,5),['合格','良好','不合格','优秀'])\n",
    "plt.box(False)\n",
    "plt.grid(axis='y',alpha=0.4)\n",
    "plt.legend(['1000米跑','跳远'])\n",
    "plt.title(label='女性1000米跑与跳远成绩分布',fontdict={'fontsize':20},color='white',backgroundcolor='black',pad=30)\n",
    "\n",
    "for ff in fig1:\n",
    "    height = ff.get_height()\n",
    "    plt.text(x=ff.get_x()+0.15,y=height+10,s=height,ha='center',fontsize=12,color='#77d109')\n",
    "for ff in fig2:\n",
    "    height = ff.get_height()\n",
    "    plt.text(x=ff.get_x()+0.15,y=height+10,s=height,ha='center',fontsize=12,color='#ff2488')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d379ae59",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 体重指数分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "7ebc04ff",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "cond1 =male['BMI']!=0\n",
    "male_clean =male[cond1]\n",
    "cond1 =female['BMI']!=0\n",
    "female_clean =female[cond1]  #先对数据进行简单清洗，未测量体重的同学先剔除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "41806c3a",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "male_weight =pd.cut(male.BMI,bins=[0,16.5,23.2,26.3,100],labels=['低体重','正常','超重','肥胖']).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "8fe7ff15",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "female_weight =pd.cut(female.BMI,bins=[0,16.5,22.7,25.2,100],labels=['低体重','正常','超重','肥胖']).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "4d4baa6d",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "total_BMI =female_weight+male_weight #将全部样本合并"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 444,
   "id": "f30a557e",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1ab84290a08>"
      ]
     },
     "execution_count": 444,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,6),dpi=100)\n",
    "_=plt.pie(total_BMI,radius=0.9,autopct='%0.2f%%',pctdistance=1.25,labels=total_BMI.index,labeldistance=1.4,\n",
    "          textprops={'fontsize':10},wedgeprops={'linewidth':3,'width':0.25,'edgecolor':'white'})\n",
    "\n",
    "_=plt.pie(tol_index,radius=0.7,autopct='%0.2f%%',pctdistance=0.8,\n",
    "          textprops={'fontsize':7},wedgeprops={'linewidth':3,'width':0.25,'edgecolor':'white'})\n",
    "\n",
    "plt.legend(['正常','超重','肥胖','低体重'],loc=3,fontsize=10)\n",
    "plt.legend(['女正常','男正常','女超重','男超重','男肥胖 ','女肥胖','男低体重 ','女低体重'],loc=3,fontsize=7.5) #可以正常生成标签，但无法对应，麻烦老师给出具体方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "id": "dd8e2674",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "# t = pd.concat([male_weight,female_weight])\n",
    "# t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "id": "e1654cd1",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "total = pd.concat([male,female])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "id": "60091d47",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "T =total[['性别','BMI']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 420,
   "id": "048ae7bf",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "male_index =pd.DataFrame(pd.cut(male.BMI,bins=[0,16.5,23.2,26.3,100],labels=['男低体重','男正常','男超重','男肥胖']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "id": "9cb8f8f9",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>女正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>女超重</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>女超重</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>女正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>女正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>588</th>\n",
       "      <td>女正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>589</th>\n",
       "      <td>女正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>590</th>\n",
       "      <td>女正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>591</th>\n",
       "      <td>女正常</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592</th>\n",
       "      <td>女正常</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>593 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     BMI\n",
       "0    女正常\n",
       "1    女超重\n",
       "2    女超重\n",
       "3    女正常\n",
       "4    女正常\n",
       "..   ...\n",
       "588  女正常\n",
       "589  女正常\n",
       "590  女正常\n",
       "591  女正常\n",
       "592  女正常\n",
       "\n",
       "[593 rows x 1 columns]"
      ]
     },
     "execution_count": 426,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "female_index =pd.DataFrame(pd.cut(female.BMI,bins=[0,16.5,23.2,26.3,100],labels=['女低体重','女正常','女超重','女肥胖']))\n",
    "female_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 413,
   "id": "7575b3bc",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "# for i in T.iloc[:,0]:\n",
    "#     if i =='男':\n",
    "#         T['group']=pd.cut(T.BMI,bins=[0,16.5,23.2,26.3,100],labels=['男低体重','男正常','男超重','男肥胖'])\n",
    "#     else :\n",
    "#         T['group']=pd.cut(T.BMI,bins=[0,16.5,23.2,26.3,100],labels=['女低体重','女正常','女超重','女肥胖'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "id": "4722ea7d",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "tol_index =pd.concat([male_index,female_index])\n",
    "tol_index =tol_index.value_counts() #将男女分别的体重类别筛选出来"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 431,
   "id": "67a8c0f9",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BMI \n",
       "女正常     465\n",
       "男正常     352\n",
       "女超重      79\n",
       "男超重      61\n",
       "男肥胖      38\n",
       "女肥胖      31\n",
       "男低体重     15\n",
       "女低体重     11\n",
       "dtype: int64"
      ]
     },
     "execution_count": 431,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tol_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "68c7e388",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": []
  }
 ],
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